Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in 5 overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively derived search strategies. Using a case study and selected examples, we then reflect on the utility of certain technologies (term frequency–inverse document frequency and Termine, term frequency, and clustering) in improving the precision and sensitivity of searches. Challenges in using these tools are discussed. The utility of these tools is influenced by the different capabilities of the tools, the way the tools are used, and the text that is analysed. Increased awareness of how the tools perform facilitates the further development of methods for their use in systematic reviews.

中文翻译：

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系统评价中搜索词开发的文本挖掘：一些方法和挑战的讨论。

使用文本挖掘来帮助开发由不同术语描述的主题的数据库搜索字符串对系统评价有潜在的好处；然而，研究方法文献中很少涵盖实现这一目标的方法和工具。我们简要回顾了有关将文本挖掘应用于搜索词开发以进行系统审查的文献。我们发现这些工具可用于 5 种总体方式：提高搜索的精确度；识别搜索词以提高搜索灵敏度；帮助翻译跨数据库的搜索策略；在集成系统中搜索和筛选；并制定客观派生的搜索策略。通过案例研究和选定的示例，我们然后反思某些技术的效用（词频-逆文档频率和 Termine，词频和聚类）以提高搜索的精度和灵敏度。讨论了使用这些工具的挑战。这些工具的实用性受工具的不同功能、工具的使用方式以及所分析的文本的影响。提高对工具如何执行的认识有助于进一步开发用于系统评价的方法。